Development of Automatic Techniques for Refugee Camps Monitoring using Very High Spatial Resolution (VHSR) Satellite Imagery

Laneve, Giovanni; Santilli, Giancarlo; Lingenfelder, Iris

doi:10.1109/igarss.2006.216

Cited by 9 publications

(8 citation statements)

References 5 publications

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“…Various automated processes for feature extraction have proved to be successful (Bjorgo 2000b, Giada et al 2003, Lang et al 2006a) using mathematical morphology (Heijmans 1994), object-based image analysis (OBIA; Blaschke et al 2008) or comparative techniques (Laneve et al 2006, Lang et al 2006b. Although many of the detectable structures provide evidence of human presence, deriving reliable information on the actual number of people present or on their specific composition and dynamics is not easy or may even 5712…”

Section: Earth Observation (Eo) For Population Estimation and Camp Anmentioning

confidence: 99%

Earth observation (EO)-basedex postassessment of internally displaced person (IDP) camp evolution and population dynamics in Zam Zam, Darfur

Lang¹,

Tiede

Hölbling

et al. 2010

International Journal of Remote Sensing

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During humanitarian crises, when population figures are often urgently required but very difficult to obtain, remote sensing is able to provide evidence of both present and past population numbers. This research, conducted on QuickBird time-series imagery of the Zam Zam internally displaced person (IDP) camp in Northern Darfur, investigates automated analysis of the camp's evolution between 2002 and 2008, including delineation of the camp's outlines and inner structure, employment of rule-based extraction for two categories of dwelling units and derivation of population estimates for the time of image capture. Reference figures for dwelling occupancy were obtained from estimates made by aid agencies. Although validation of such 'ondemand' census techniques is still continuing, the benefits of a fast, efficient and objective information source are obvious. Spatial, as well thematic, accuracy was, in this instance, assessed against visual interpretation of eight 200 m Â 200 m grid cells and accuracy statistics calculated. Total user's and producer's accuracy rates ranged from 71.6% up to 94.9%. While achieving promising results with respect to accuracy, transferability and usability, the remaining limitations of automated population estimation in dynamic crisis situations will provide a stimulus for future research.

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Section: Earth Observation (Eo) For Population Estimation and Camp Anmentioning

confidence: 99%

Earth observation (EO)-basedex postassessment of internally displaced person (IDP) camp evolution and population dynamics in Zam Zam, Darfur

Lang¹,

Tiede

Hölbling

et al. 2010

International Journal of Remote Sensing

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“…With technological progress, the spatial resolution of the sensors increased, and new methods were developed which helped to automate such tasks. Among the most important were the object-based analysis of very high-resolution (VHR) images of refugee camps (Hagenlocher et al, 2012;Lang et al, 2010;Spröhnle et al, 2017), methods of template matching and machine learning (Ghorbanzadeh et al, 2018;Laneve et al, 2006;Quinn et al, 2018;Tiede et al, 2017), and studies based on synthetic aperture radar (SAR) images (Amitrano et al, 2013;Braun, 2018;. However, most of the approaches deal with the observation of land use and landcover as well as their socio-economic implications.…”

Section: Background and Aimsmentioning

confidence: 99%

Elevation change of Bhasan Char measured by persistent scatterer interferometry using Sentinel-1 data in a humanitarian context

Braun

Hoeser

Blasco

2020

European Journal of Remote Sensing

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This study investigates the elevation changes for the island of Bhasan Char, located in the Bay of Bengal, which was selected for the relocation of around 100,000 refugees of the Rohingya minority which were forced to leave their homes in Myanmar. Eighty-nine Sentinel-1 products were analysed using persistent scatterer interferometry (PSI) beginning August 2016 through September 2019, divided into three periods of one year to reduce the impact of temporal decorrelation. The findings indicate that the island is a recent landform which underlies naturally induced surface changes with velocities of up to ±20 mm per year. Additional displacement is probably caused by heavy construction loads since early 2018, although we found no statistical evidence for this. The main built-up area shows stable behaviour during the analysed period, but there are significant changes along the coasts and artificial embankments of the island, and within one separate settlement in the north. The moist surface conditions and strong monsoonal rains complicated the proper retrieval of stable trends, but the sum of findings supports the assumption that the island underlies strong morphologic dynamics which put the people to be relocated at additional risk. Its suitability for construction has to be investigated in further studies.

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“…In general, the quality of pre-event data from crowdsourcing was quite good, but on post-event data volunteer mappers tended to map many damages, which were not evident, meaning that they tended to include more commission errors. In order to cope with the requirements of achieving reliable, transferable, yet quick and objective results, new methods of automated information extraction have been investigated in the humanitarian context in recent years (Laneve, Santilli, & Lingenfelder, 2006;Lang et al, 2010;Spröhnle, Fuchs, & Pelizari, 2017;Spröhnle et al, 2014;Tiede et al, 2013).…”

Section: Information Extraction and Analysismentioning

confidence: 99%

“…the process of finding a pattern in an image, is widely used in remote sensing to address a variety of problems including road extraction (Hu, Zhang, & Tao, 2004) or dwelling detection. The integration of stratified template matching methods in an OBIA workflow has shown to improve the accuracy of dwelling extraction (Laneve et al, 2006;Tiede, Krafft, Füreder, & Lang, 2017).…”

Section: Information Extraction and Analysismentioning

confidence: 99%

Earth observation tools and services to increase the effectiveness of humanitarian assistance

Lang

Füreder

Riedler

et al. 2019

European Journal of Remote Sensing

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Humanitarian action has rapidly adopted Earth observation (EO) and geospatial technologies shaping them according to their needs. Protracted crises and large-scale population displacements require up-to-date information in many facets of humanitarian action support, from mission planning, resource deployment and monitoring, to nutrition and vaccination campaigns, camp plotting, damage assessment, etc. Even though nearly all assets of remote sensing apply in such demanding scenarios, it remains a challenge to fully implement and sustain a trustful and reliable information service. This paper discusses achievements and open issues in the use and uptake of EO technology, from a technical and organisational point of view, motivated by an information service for Médecins Sans Frontières (MSF) and its extension to other NGO's information needs in the humanitarian sector. With a focus on EO-based population estimation based on (semi-)automated dwelling counting from very high-resolution optical satellite imagery as well as the exploitation of data integration (including radar sensors), the paper also covers potential service elements with respect to environmental and ground-or surface water monitoring. It investigates workflow elements in relation to information extraction and delivery by illustrating a broad range of application scenarios, and discusses first operational solutions of a customized service portfolio.

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Development of Automatic Techniques for Refugee Camps Monitoring using Very High Spatial Resolution (VHSR) Satellite Imagery

Cited by 9 publications

References 5 publications

Earth observation (EO)-basedex postassessment of internally displaced person (IDP) camp evolution and population dynamics in Zam Zam, Darfur

Earth observation (EO)-basedex postassessment of internally displaced person (IDP) camp evolution and population dynamics in Zam Zam, Darfur

Elevation change of Bhasan Char measured by persistent scatterer interferometry using Sentinel-1 data in a humanitarian context

Earth observation tools and services to increase the effectiveness of humanitarian assistance

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